Integrating Pharmacogenetics into Pv Systems: Current Landscape and Future Prospects

BackgroundPharmacovigilance (PV) is essential for detecting and preventing adverse drug reactions (ADRs), yet traditional systems suffer from underreporting and limited insights into individual risk factors. Pharmacogenetics (PGx) offers a promising approach by linking genetic variations to drug responses, enabling precision pv. Despite advancements, challenges such as fragmented data systems, genomic inequities, and implementation barriers persist.ObjectiveThis scoping review followed the PRISMA-ScR guideline to map existing evidence and implementation models linking PGx with PV. The review focuses on (1) regulatory and guideline progress, (2) operational models and technological enablers (e.g., AI-enhanced signal detection), and (3) implementation barriers (data fragmentation, genomic disparities, and ethical concerns).MethodsThe review followed PRISMA-ScR methodology and was registered on the Open Science Framework (OSF). A comprehensive search of the Egyptian Knowledge Bank (EKB) databases (Elsevier, Sage, Springer/Nature, Wiley), PubMed, and Medline covered January 2023–August 2025. Two reviewers (Mohammed G. Maslub, PhD and Abubakar Shaaban, PhD) independently screened titles, abstracts, and full texts. Data were charted according to study design, objectives, PGx–PV integration approach, and outcomes. Critical appraisal used the JBI checklist for scoping reviews.ResultsFrom 728,621 initial records (489,331 from EKB + 239,290 from PubMed/Medline), 26 studies met inclusion criteria (English, peer-reviewed, real-world applications). These included real-world pharmacogenomic applications, clinical decision support integration, and AI-enhanced PV models. The analysis revealed that 9% of the ADRs in the yellow card system of the UK involved pharmacogenetically actionable drugs (e.g., CYP2C19 and CYP2D6), with preemptive genotyping reducing ADRs by 30% in clinical trials. AI approaches such as the CNN-BERT model achieved 85% ADR detection accuracy, while implementation programs identified thousands of actionable variants. However, adoption remains inconsistent (only 11% in elderly polypharmacy patients), and significant gaps persist in global representation, particularly for African populations with unique PGx variants (e.g., NAT2, CYP2E1).ConclusionPGx-enhanced PV improves ADR prediction and prevention, with success in cardiology (CYP2C19-clopidogrel) and oncology (DPYD testing). However, challenges include data inequities, AI validation gaps, and implementation barriers. This scoping review identifies key implementation enablers and barriers to guide future precision PV research.